Update README.md

README.md

@@ -1,6 +1,5 @@
 ---
 library_name: transformers
-tags: []
 model-index:
 - name: internlm-chatbode-20b
   results:
@@ -18,7 +17,8 @@ model-index:
       value: 65.78
       name: accuracy
     source:
-      url: https://huggingface.co/spaces/eduagarcia/open_pt_llm_leaderboard?query=recogna-nlp/internlm-chatbode-20b
+      url: >-
+        https://huggingface.co/spaces/eduagarcia/open_pt_llm_leaderboard?query=recogna-nlp/internlm-chatbode-20b
       name: Open Portuguese LLM Leaderboard
   - task:
       type: text-generation
@@ -34,7 +34,8 @@ model-index:
       value: 58.69
       name: accuracy
     source:
-      url: https://huggingface.co/spaces/eduagarcia/open_pt_llm_leaderboard?query=recogna-nlp/internlm-chatbode-20b
+      url: >-
+        https://huggingface.co/spaces/eduagarcia/open_pt_llm_leaderboard?query=recogna-nlp/internlm-chatbode-20b
       name: Open Portuguese LLM Leaderboard
   - task:
       type: text-generation
@@ -50,7 +51,8 @@ model-index:
       value: 43.33
       name: accuracy
     source:
-      url: https://huggingface.co/spaces/eduagarcia/open_pt_llm_leaderboard?query=recogna-nlp/internlm-chatbode-20b
+      url: >-
+        https://huggingface.co/spaces/eduagarcia/open_pt_llm_leaderboard?query=recogna-nlp/internlm-chatbode-20b
       name: Open Portuguese LLM Leaderboard
   - task:
       type: text-generation
@@ -66,7 +68,8 @@ model-index:
       value: 91.53
       name: f1-macro
     source:
-      url: https://huggingface.co/spaces/eduagarcia/open_pt_llm_leaderboard?query=recogna-nlp/internlm-chatbode-20b
+      url: >-
+        https://huggingface.co/spaces/eduagarcia/open_pt_llm_leaderboard?query=recogna-nlp/internlm-chatbode-20b
       name: Open Portuguese LLM Leaderboard
   - task:
       type: text-generation
@@ -82,7 +85,8 @@ model-index:
       value: 78.95
       name: pearson
     source:
-      url: https://huggingface.co/spaces/eduagarcia/open_pt_llm_leaderboard?query=recogna-nlp/internlm-chatbode-20b
+      url: >-
+        https://huggingface.co/spaces/eduagarcia/open_pt_llm_leaderboard?query=recogna-nlp/internlm-chatbode-20b
       name: Open Portuguese LLM Leaderboard
   - task:
       type: text-generation
@@ -98,7 +102,8 @@ model-index:
       value: 81.36
       name: f1-macro
     source:
-      url: https://huggingface.co/spaces/eduagarcia/open_pt_llm_leaderboard?query=recogna-nlp/internlm-chatbode-20b
+      url: >-
+        https://huggingface.co/spaces/eduagarcia/open_pt_llm_leaderboard?query=recogna-nlp/internlm-chatbode-20b
       name: Open Portuguese LLM Leaderboard
   - task:
       type: text-generation
@@ -114,7 +119,8 @@ model-index:
       value: 81.72
       name: f1-macro
     source:
-      url: https://huggingface.co/spaces/eduagarcia/open_pt_llm_leaderboard?query=recogna-nlp/internlm-chatbode-20b
+      url: >-
+        https://huggingface.co/spaces/eduagarcia/open_pt_llm_leaderboard?query=recogna-nlp/internlm-chatbode-20b
       name: Open Portuguese LLM Leaderboard
   - task:
       type: text-generation
@@ -130,7 +136,8 @@ model-index:
       value: 73.66
       name: f1-macro
     source:
-      url: https://huggingface.co/spaces/eduagarcia/open_pt_llm_leaderboard?query=recogna-nlp/internlm-chatbode-20b
+      url: >-
+        https://huggingface.co/spaces/eduagarcia/open_pt_llm_leaderboard?query=recogna-nlp/internlm-chatbode-20b
       name: Open Portuguese LLM Leaderboard
   - task:
       type: text-generation
@@ -146,204 +153,58 @@ model-index:
       value: 70.11
       name: f1-macro
     source:
-      url: https://huggingface.co/spaces/eduagarcia/open_pt_llm_leaderboard?query=recogna-nlp/internlm-chatbode-20b
+      url: >-
+        https://huggingface.co/spaces/eduagarcia/open_pt_llm_leaderboard?query=recogna-nlp/internlm-chatbode-20b
       name: Open Portuguese LLM Leaderboard
+language:
+- pt
+pipeline_tag: text-generation
 ---
 
-# Model Card for Model ID
+# internlm-chatbode-20b
 
 <!-- Provide a quick summary of what the model is/does. -->
 
+O InternLm-ChatBode é um modelo de linguagem ajustado para o idioma português, desenvolvido a partir do modelo [InternLM2](https://huggingface.co/internlm/internlm2-chat-20b). Este modelo foi refinado através do processo de fine-tuning utilizando o dataset UltraAlpaca.
 
+## Características Principais
 
-## Model Details
+- **Modelo Base:** [internlm/internlm2-chat-20b](internlm/internlm2-chat-20b)
+- **Dataset para Fine-tuning:** UltraAlpaca
+- **Treinamento:** O treinamento foi realizado a partir do fine-tuning, usando QLoRA, do internlm2-chat-20b.
 
-### Model Description
+## Exemplo de uso
 
-<!-- Provide a longer summary of what this model is. -->
+A seguir um exemplo de código de como carregar e utilizar o modelo:
 
-This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated.
+```python
+import torch
+from transformers import AutoTokenizer, AutoModelForCausalLM
+tokenizer = AutoTokenizer.from_pretrained("recogna-nlp/internlm-chatbode-20b", trust_remote_code=True)
+model = AutoModelForCausalLM.from_pretrained("recogna-nlp/internlm-chatbode-20b", torch_dtype=torch.float16, trust_remote_code=True).cuda()
+model = model.eval()
+response, history = model.chat(tokenizer, "Olá", history=[])
+print(response)
+response, history = model.chat(tokenizer, "O que é o Teorema de Pitágoras? Me dê um exemplo", history=history)
+print(response)
+```
 
-- **Developed by:** [More Information Needed]
-- **Funded by [optional]:** [More Information Needed]
-- **Shared by [optional]:** [More Information Needed]
-- **Model type:** [More Information Needed]
-- **Language(s) (NLP):** [More Information Needed]
-- **License:** [More Information Needed]
-- **Finetuned from model [optional]:** [More Information Needed]
+As respostas podem ser geradas via stream utilizando o método `stream_chat`:
 
-### Model Sources [optional]
+```python
+import torch
+from transformers import AutoModelForCausalLM, AutoTokenizer
 
-<!-- Provide the basic links for the model. -->
+model_path = "recogna-nlp/internlm-chatbode-20b"
+model = AutoModelForCausalLM.from_pretrained(model_path, torch_dtype=torch.float16, trust_remote_code=True).cuda()
+tokenizer = AutoTokenizer.from_pretrained(model_path, trust_remote_code=True)
 
-- **Repository:** [More Information Needed]
-- **Paper [optional]:** [More Information Needed]
-- **Demo [optional]:** [More Information Needed]
-
-## Uses
-
-<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
-
-### Direct Use
-
-<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
-
-[More Information Needed]
-
-### Downstream Use [optional]
-
-<!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
-
-[More Information Needed]
-
-### Out-of-Scope Use
-
-<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
-
-[More Information Needed]
-
-## Bias, Risks, and Limitations
-
-<!-- This section is meant to convey both technical and sociotechnical limitations. -->
-
-[More Information Needed]
-
-### Recommendations
-
-<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
-
-Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
-
-## How to Get Started with the Model
-
-Use the code below to get started with the model.
-
-[More Information Needed]
-
-## Training Details
-
-### Training Data
-
-<!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
-
-[More Information Needed]
-
-### Training Procedure
-
-<!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
-
-#### Preprocessing [optional]
-
-[More Information Needed]
-
-
-#### Training Hyperparameters
-
-- **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
-
-#### Speeds, Sizes, Times [optional]
-
-<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
-
-[More Information Needed]
-
-## Evaluation
-
-<!-- This section describes the evaluation protocols and provides the results. -->
-
-### Testing Data, Factors & Metrics
-
-#### Testing Data
-
-<!-- This should link to a Dataset Card if possible. -->
-
-[More Information Needed]
-
-#### Factors
-
-<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
-
-[More Information Needed]
-
-#### Metrics
-
-<!-- These are the evaluation metrics being used, ideally with a description of why. -->
-
-[More Information Needed]
-
-### Results
-
-[More Information Needed]
-
-#### Summary
-
-
-
-## Model Examination [optional]
-
-<!-- Relevant interpretability work for the model goes here -->
-
-[More Information Needed]
-
-## Environmental Impact
-
-<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
-
-Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
-
-- **Hardware Type:** [More Information Needed]
-- **Hours used:** [More Information Needed]
-- **Cloud Provider:** [More Information Needed]
-- **Compute Region:** [More Information Needed]
-- **Carbon Emitted:** [More Information Needed]
-
-## Technical Specifications [optional]
-
-### Model Architecture and Objective
-
-[More Information Needed]
-
-### Compute Infrastructure
-
-[More Information Needed]
-
-#### Hardware
-
-[More Information Needed]
-
-#### Software
-
-[More Information Needed]
-
-## Citation [optional]
-
-<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
-
-**BibTeX:**
-
-[More Information Needed]
-
-**APA:**
-
-[More Information Needed]
-
-## Glossary [optional]
-
-<!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
-
-[More Information Needed]
-
-## More Information [optional]
-
-[More Information Needed]
-
-## Model Card Authors [optional]
-
-[More Information Needed]
-
-## Model Card Contact
-
-[More Information Needed]
+model = model.eval()
+length = 0
+for response, history in model.stream_chat(tokenizer, "Olá", history=[]):
+    print(response[length:], flush=True, end="")
+    length = len(response)
+```
 
 
 # Open Portuguese LLM Leaderboard Evaluation Results  
@@ -361,5 +222,4 @@ Detailed results can be found [here](https://huggingface.co/datasets/eduagarcia-
 |FaQuAD NLI                |    81.36|
 |HateBR Binary             |    81.72|
 |PT Hate Speech Binary     |    73.66|
-|tweetSentBR               |    70.11|
-
+|tweetSentBR               |    70.11|